# hoya012/awesome-anomaly-detection

A curated list of awesome anomaly detection resources

Repository: https://github.com/hoya012/awesome-anomaly-detection
Canonical: https://ross.abutalabs.com/products/awesome-anomaly-detection
License Family: other
Topics: awesome-anomaly-detection, awesome, anomaly-detection, anomalydetection, anomaly, deep-learning, awesomeanomalydetection, machine-learning, machinelearning
Last push: 2022-09-20T09:33:40+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2926, "days_push": 1443, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2901, forks 510 (observed 2026-08-28T04:07:28.902900+00:00)

## What it is
A curated list of anomaly detection resources including survey papers, research papers, and datasets organized by data type (time-series, video, image). It covers related topics like novelty detection, outlier detection, and out-of-distribution detection.

## Use cases
- find papers on anomaly detection
- learn about deep learning for anomaly detection
- find anomaly detection datasets
- research out-of-distribution detection methods
- find time-series anomaly detection resources
- get started with outlier detection research

## When to choose
- you need a starting point for anomaly detection research
- you want curated survey papers on novelty or outlier detection
- you are looking for datasets for anomaly detection benchmarks

## When to avoid
- you need a working anomaly detection library or tool
- you need up-to-date resources, as the list was last updated in 2021
- you need practical code examples rather than paper links

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: machine-learning, deep-learning, documentation
- domain: machine-learning, deep-learning, artificial-intelligence, tutorials, awesome-lists
- platform: cross-platform
- tags: anomaly-detection, curated-list, papers, outlier-detection, novelty-detection, survey-papers, time-series, computer-vision

## Member repositories
- hoya012/awesome-anomaly-detection (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:28.902900+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T07:35:09.892877+00:00, confidence not recorded.
  - readme: https://github.com/hoya012/awesome-anomaly-detection (fetched 2026-08-28T04:07:28.902900+00:00, sha 179d4c66c2a7)
- Data as of 2026-08-30T08:39:29.467469+00:00.